From ee4e4d04b2dc24bcbd2de0eeb71cfd23d4ecad6e Mon Sep 17 00:00:00 2001
From: Martin Liska <martin.liska@hey.com>
Date: Wed, 5 Mar 2025 07:58:12 +0100
Subject: [PATCH] Add plot_benchmarks scripts

The script is intended for a collection of hyperfine JSON files where
multiple benchmarks were run for a selected group of commands.
---
 scripts/plot_benchmarks.py | 80 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 80 insertions(+)
 create mode 100755 scripts/plot_benchmarks.py

diff --git a/scripts/plot_benchmarks.py b/scripts/plot_benchmarks.py
new file mode 100755
index 0000000..3c81ba8
--- /dev/null
+++ b/scripts/plot_benchmarks.py
@@ -0,0 +1,80 @@
+#!/usr/bin/env python
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "matplotlib",
+#     "pyqt6",
+#     "numpy",
+# ]
+# ///
+
+# This program shows `hyperfine` benchmark results as a bar plot grouped by command.
+
+import argparse
+import json
+import pathlib
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+parser = argparse.ArgumentParser(description=__doc__)
+parser.add_argument(
+    "files", nargs="+", type=pathlib.Path, help="JSON files with benchmark results"
+)
+parser.add_argument("--title", help="Plot Title")
+parser.add_argument(
+    "--benchmark-names", nargs="+", help="Names of the benchmark groups"
+)
+parser.add_argument("-o", "--output", help="Save image to the given filename")
+
+args = parser.parse_args()
+
+commands = None
+data = []
+inputs = []
+
+if args.benchmark_names:
+    assert len(args.files) == len(
+        args.benchmark_names
+    ), "Number of benchmark names must match the number of input files."
+
+for i, filename in enumerate(args.files):
+    with open(filename) as f:
+        results = json.load(f)["results"]
+    benchmark_commands = [b["command"] for b in results]
+    if commands is None:
+        commands = benchmark_commands
+    else:
+        assert (
+            commands == benchmark_commands
+        ), f"Unexpected commands in {filename}: {benchmark_commands}, expected: {commands}"
+    data.append([round(b["mean"], 2) for b in results])
+    if args.benchmark_names:
+        inputs.append(args.benchmark_names[i])
+    else:
+        inputs.append(filename.stem)
+
+data = np.transpose(data)
+x = np.arange(len(inputs))  # the label locations
+width = 0.25  # the width of the bars
+
+fig, ax = plt.subplots(layout="constrained")
+fig.set_figheight(5)
+fig.set_figwidth(10)
+for i, command in enumerate(commands):
+    offset = width * (i + 1)
+    rects = ax.bar(x + offset, data[i], width, label=command)
+
+ax.set_xticks(x + 0.5, inputs)
+ax.grid(visible=True, axis="y")
+
+if args.title:
+    plt.title(args.title)
+plt.xlabel("Benchmark")
+plt.ylabel("Time [s]")
+plt.legend(title="Command")
+
+if args.output:
+    plt.savefig(args.output)
+else:
+    plt.show()